Overview

Dataset statistics

Number of variables10
Number of observations4990
Missing cells0
Missing cells (%)0.0%
Total size in memory428.8 KiB
Average record size in memory88.0 B

Variable types

Numeric10

Alerts

carat is highly overall correlated with price and 3 other fieldsHigh correlation
price is highly overall correlated with carat and 3 other fieldsHigh correlation
x is highly overall correlated with carat and 3 other fieldsHigh correlation
y is highly overall correlated with carat and 3 other fieldsHigh correlation
z is highly overall correlated with carat and 3 other fieldsHigh correlation
cut has 158 (3.2%) zerosZeros
color has 248 (5.0%) zerosZeros
clarity has 64 (1.3%) zerosZeros

Reproduction

Analysis started2024-04-24 16:54:26.495952
Analysis finished2024-04-24 16:54:34.147294
Duration7.65 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

carat
Real number (ℝ)

HIGH CORRELATION 

Distinct202
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.79401804
Minimum0.23
Maximum4.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:34.200017image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.23
5-th percentile0.3
Q10.4
median0.7
Q31.04
95-th percentile1.67
Maximum4.13
Range3.9
Interquartile range (IQR)0.64

Descriptive statistics

Standard deviation0.46798638
Coefficient of variation (CV)0.58939011
Kurtosis1.1572604
Mean0.79401804
Median Absolute Deviation (MAD)0.32
Skewness1.0762322
Sum3962.15
Variance0.21901125
MonotonicityNot monotonic
2024-04-24T13:54:34.301032image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3 250
 
5.0%
1.01 228
 
4.6%
0.31 207
 
4.1%
0.32 192
 
3.8%
0.7 167
 
3.3%
0.9 143
 
2.9%
1 142
 
2.8%
0.41 124
 
2.5%
0.4 121
 
2.4%
0.5 117
 
2.3%
Other values (192) 3299
66.1%
ValueCountFrequency (%)
0.23 37
 
0.7%
0.24 12
 
0.2%
0.25 17
 
0.3%
0.26 30
 
0.6%
0.27 24
 
0.5%
0.28 14
 
0.3%
0.29 12
 
0.2%
0.3 250
5.0%
0.31 207
4.1%
0.32 192
3.8%
ValueCountFrequency (%)
4.13 1
< 0.1%
3.01 2
< 0.1%
2.53 1
< 0.1%
2.52 2
< 0.1%
2.51 1
< 0.1%
2.5 2
< 0.1%
2.48 1
< 0.1%
2.47 1
< 0.1%
2.44 1
< 0.1%
2.42 2
< 0.1%

cut
Real number (ℝ)

ZEROS 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7611222
Minimum0
Maximum4
Zeros158
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:34.384793image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.0354759
Coefficient of variation (CV)0.37501995
Kurtosis-0.036761531
Mean2.7611222
Median Absolute Deviation (MAD)1
Skewness-0.68966193
Sum13778
Variance1.0722104
MonotonicityNot monotonic
2024-04-24T13:54:34.459866image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
3 1988
39.8%
4 1291
25.9%
2 1097
22.0%
1 456
 
9.1%
0 158
 
3.2%
ValueCountFrequency (%)
0 158
 
3.2%
1 456
 
9.1%
2 1097
22.0%
3 1988
39.8%
4 1291
25.9%
ValueCountFrequency (%)
4 1291
25.9%
3 1988
39.8%
2 1097
22.0%
1 456
 
9.1%
0 158
 
3.2%

color
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3921844
Minimum0
Maximum6
Zeros248
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:34.534243image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6912101
Coefficient of variation (CV)0.49856077
Kurtosis-0.86816693
Mean3.3921844
Median Absolute Deviation (MAD)1
Skewness-0.17065934
Sum16927
Variance2.8601915
MonotonicityNot monotonic
2024-04-24T13:54:34.603223image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3 1095
21.9%
5 917
18.4%
4 843
16.9%
2 763
15.3%
6 607
12.2%
1 517
10.4%
0 248
 
5.0%
ValueCountFrequency (%)
0 248
 
5.0%
1 517
10.4%
2 763
15.3%
3 1095
21.9%
4 843
16.9%
5 917
18.4%
6 607
12.2%
ValueCountFrequency (%)
6 607
12.2%
5 917
18.4%
4 843
16.9%
3 1095
21.9%
2 763
15.3%
1 517
10.4%
0 248
 
5.0%

clarity
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0597194
Minimum0
Maximum7
Zeros64
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:34.674643image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.632269
Coefficient of variation (CV)0.53347016
Kurtosis-0.41489066
Mean3.0597194
Median Absolute Deviation (MAD)1
Skewness0.52608155
Sum15268
Variance2.6643022
MonotonicityNot monotonic
2024-04-24T13:54:34.749574image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 1191
23.9%
3 1131
22.7%
1 843
16.9%
4 801
16.1%
5 464
 
9.3%
6 346
 
6.9%
7 150
 
3.0%
0 64
 
1.3%
ValueCountFrequency (%)
0 64
 
1.3%
1 843
16.9%
2 1191
23.9%
3 1131
22.7%
4 801
16.1%
5 464
 
9.3%
6 346
 
6.9%
7 150
 
3.0%
ValueCountFrequency (%)
7 150
 
3.0%
6 346
 
6.9%
5 464
 
9.3%
4 801
16.1%
3 1131
22.7%
2 1191
23.9%
1 843
16.9%
0 64
 
1.3%

depth
Real number (ℝ)

Distinct121
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.710741
Minimum44
Maximum70.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:34.843572image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile59.2
Q161
median61.8
Q362.5
95-th percentile63.8
Maximum70.2
Range26.2
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.445436
Coefficient of variation (CV)0.023422762
Kurtosis7.1154314
Mean61.710741
Median Absolute Deviation (MAD)0.7
Skewness-0.4492632
Sum307936.6
Variance2.0892853
MonotonicityNot monotonic
2024-04-24T13:54:34.943907image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62 225
 
4.5%
61.6 203
 
4.1%
62.1 193
 
3.9%
62.2 191
 
3.8%
61.9 186
 
3.7%
62.3 182
 
3.6%
61.8 178
 
3.6%
61.5 177
 
3.5%
61.7 169
 
3.4%
61.3 147
 
2.9%
Other values (111) 3139
62.9%
ValueCountFrequency (%)
44 1
 
< 0.1%
53 1
 
< 0.1%
55.3 1
 
< 0.1%
55.8 2
< 0.1%
55.9 1
 
< 0.1%
56.3 3
0.1%
56.5 2
< 0.1%
56.6 1
 
< 0.1%
56.7 3
0.1%
56.8 3
0.1%
ValueCountFrequency (%)
70.2 1
< 0.1%
69.8 2
< 0.1%
69.6 1
< 0.1%
68.6 1
< 0.1%
68.5 1
< 0.1%
68.1 1
< 0.1%
67.9 1
< 0.1%
67.8 1
< 0.1%
67.6 2
< 0.1%
67.5 1
< 0.1%

table
Real number (ℝ)

Distinct78
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.446152
Minimum51.6
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:35.043368image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum51.6
5-th percentile54
Q156
median57
Q359
95-th percentile61
Maximum95
Range43.4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2595345
Coefficient of variation (CV)0.039333088
Kurtosis15.529192
Mean57.446152
Median Absolute Deviation (MAD)1
Skewness1.4790147
Sum286656.3
Variance5.1054963
MonotonicityNot monotonic
2024-04-24T13:54:35.138505image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56 918
18.4%
57 889
17.8%
58 765
15.3%
59 640
12.8%
55 584
11.7%
60 361
 
7.2%
54 236
 
4.7%
61 209
 
4.2%
62 121
 
2.4%
63 59
 
1.2%
Other values (68) 208
 
4.2%
ValueCountFrequency (%)
51.6 1
 
< 0.1%
52 6
 
0.1%
53 50
1.0%
53.1 1
 
< 0.1%
53.3 1
 
< 0.1%
53.4 1
 
< 0.1%
53.5 2
 
< 0.1%
53.6 1
 
< 0.1%
53.7 2
 
< 0.1%
53.8 5
 
0.1%
ValueCountFrequency (%)
95 1
 
< 0.1%
70 1
 
< 0.1%
68 1
 
< 0.1%
67 1
 
< 0.1%
66 7
 
0.1%
65.4 1
 
< 0.1%
65 8
 
0.2%
64.2 1
 
< 0.1%
64 26
0.5%
63 59
1.2%

price
Real number (ℝ)

HIGH CORRELATION 

Distinct3177
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3929.9255
Minimum351
Maximum18787
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:35.231233image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum351
5-th percentile544
Q1942
median2397
Q35375.25
95-th percentile12925.15
Maximum18787
Range18436
Interquartile range (IQR)4433.25

Descriptive statistics

Standard deviation3970.7961
Coefficient of variation (CV)1.0103998
Kurtosis2.0798183
Mean3929.9255
Median Absolute Deviation (MAD)1688
Skewness1.5876822
Sum19610328
Variance15767222
MonotonicityNot monotonic
2024-04-24T13:54:35.331731image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
776 15
 
0.3%
765 15
 
0.3%
605 15
 
0.3%
561 14
 
0.3%
698 14
 
0.3%
625 13
 
0.3%
526 13
 
0.3%
544 13
 
0.3%
552 12
 
0.2%
878 11
 
0.2%
Other values (3167) 4855
97.3%
ValueCountFrequency (%)
351 2
< 0.1%
357 2
< 0.1%
361 1
< 0.1%
362 1
< 0.1%
363 1
< 0.1%
367 1
< 0.1%
373 1
< 0.1%
377 1
< 0.1%
383 1
< 0.1%
384 2
< 0.1%
ValueCountFrequency (%)
18787 1
< 0.1%
18777 1
< 0.1%
18741 1
< 0.1%
18705 1
< 0.1%
18656 1
< 0.1%
18541 1
< 0.1%
18515 1
< 0.1%
18493 1
< 0.1%
18445 1
< 0.1%
18430 1
< 0.1%

x
Real number (ℝ)

HIGH CORRELATION 

Distinct473
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7259459
Minimum3.86
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:35.432367image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum3.86
5-th percentile4.29
Q14.7
median5.69
Q36.54
95-th percentile7.6155
Maximum10
Range6.14
Interquartile range (IQR)1.84

Descriptive statistics

Standard deviation1.1163279
Coefficient of variation (CV)0.19495956
Kurtosis-0.74836092
Mean5.7259459
Median Absolute Deviation (MAD)0.92
Skewness0.37792194
Sum28572.47
Variance1.2461879
MonotonicityNot monotonic
2024-04-24T13:54:35.534243image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.37 50
 
1.0%
4.38 49
 
1.0%
4.34 46
 
0.9%
4.35 45
 
0.9%
4.32 44
 
0.9%
4.31 40
 
0.8%
4.4 37
 
0.7%
4.29 35
 
0.7%
6.43 34
 
0.7%
4.39 34
 
0.7%
Other values (463) 4576
91.7%
ValueCountFrequency (%)
3.86 2
 
< 0.1%
3.88 2
 
< 0.1%
3.89 1
 
< 0.1%
3.9 2
 
< 0.1%
3.91 2
 
< 0.1%
3.92 4
0.1%
3.93 4
0.1%
3.94 6
0.1%
3.95 3
0.1%
3.96 4
0.1%
ValueCountFrequency (%)
10 1
< 0.1%
9.44 1
< 0.1%
9.24 1
< 0.1%
8.89 1
< 0.1%
8.87 1
< 0.1%
8.83 1
< 0.1%
8.8 1
< 0.1%
8.72 1
< 0.1%
8.68 1
< 0.1%
8.64 1
< 0.1%

y
Real number (ℝ)

HIGH CORRELATION 

Distinct470
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7285531
Minimum3.84
Maximum9.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:35.630886image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum3.84
5-th percentile4.29
Q14.71
median5.7
Q36.5375
95-th percentile7.5855
Maximum9.85
Range6.01
Interquartile range (IQR)1.8275

Descriptive statistics

Standard deviation1.1092175
Coefficient of variation (CV)0.19362962
Kurtosis-0.76723114
Mean5.7285531
Median Absolute Deviation (MAD)0.92
Skewness0.36930645
Sum28585.48
Variance1.2303636
MonotonicityNot monotonic
2024-04-24T13:54:35.965799image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.34 52
 
1.0%
4.39 43
 
0.9%
4.35 39
 
0.8%
4.37 39
 
0.8%
4.41 39
 
0.8%
4.32 39
 
0.8%
4.38 37
 
0.7%
4.33 36
 
0.7%
4.29 35
 
0.7%
4.4 35
 
0.7%
Other values (460) 4596
92.1%
ValueCountFrequency (%)
3.84 1
 
< 0.1%
3.89 2
 
< 0.1%
3.9 2
 
< 0.1%
3.92 1
 
< 0.1%
3.93 1
 
< 0.1%
3.94 2
 
< 0.1%
3.95 6
0.1%
3.96 5
0.1%
3.97 4
0.1%
3.98 3
0.1%
ValueCountFrequency (%)
9.85 1
< 0.1%
9.37 1
< 0.1%
9.13 1
< 0.1%
8.93 1
< 0.1%
8.87 1
< 0.1%
8.83 1
< 0.1%
8.78 1
< 0.1%
8.66 1
< 0.1%
8.65 1
< 0.1%
8.62 1
< 0.1%

z
Real number (ℝ)

HIGH CORRELATION 

Distinct303
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.533503
Minimum1.41
Maximum6.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.0 KiB
2024-04-24T13:54:36.065011image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1.41
5-th percentile2.65
Q12.9
median3.525
Q34.03
95-th percentile4.68
Maximum6.43
Range5.02
Interquartile range (IQR)1.13

Descriptive statistics

Standard deviation0.68847914
Coefficient of variation (CV)0.19484323
Kurtosis-0.71104399
Mean3.533503
Median Absolute Deviation (MAD)0.565
Skewness0.37604629
Sum17632.18
Variance0.47400352
MonotonicityNot monotonic
2024-04-24T13:54:36.161711image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.69 77
 
1.5%
2.73 72
 
1.4%
2.72 71
 
1.4%
2.7 66
 
1.3%
2.71 66
 
1.3%
2.68 64
 
1.3%
2.67 59
 
1.2%
2.74 58
 
1.2%
2.66 56
 
1.1%
4.02 56
 
1.1%
Other values (293) 4345
87.1%
ValueCountFrequency (%)
1.41 1
 
< 0.1%
2.35 1
 
< 0.1%
2.37 1
 
< 0.1%
2.38 1
 
< 0.1%
2.39 2
 
< 0.1%
2.4 2
 
< 0.1%
2.41 1
 
< 0.1%
2.42 4
 
0.1%
2.43 6
0.1%
2.44 10
0.2%
ValueCountFrequency (%)
6.43 1
< 0.1%
6.16 1
< 0.1%
5.73 1
< 0.1%
5.62 1
< 0.1%
5.6 1
< 0.1%
5.53 1
< 0.1%
5.43 1
< 0.1%
5.42 1
< 0.1%
5.41 1
< 0.1%
5.39 1
< 0.1%

Interactions

2024-04-24T13:54:33.512018image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:26.620989image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.393668image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.331234image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.085104image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.822599image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.530612image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.195734image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.900381image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.837287image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.578102image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:26.716728image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.471332image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.400724image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.165879image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.898918image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.600699image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.269970image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.217368image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.909367image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.648650image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:26.840604image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.550167image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.474151image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.247318image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.975184image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.676699image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.345984image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.290349image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.982597image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.710460image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:26.913553image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.820523image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.539388image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.316854image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.047669image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.744171image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.415768image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.359101image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.050632image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.777534image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:26.987481image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.912571image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.608480image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.393240image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.119640image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.812928image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.487468image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.431690image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.119983image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.839320image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.053372image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.982994image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.673162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.463952image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.188084image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.875305image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.556773image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.504071image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.186078image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.899656image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.117685image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.049425image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.757116image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.533593image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.253118image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.936685image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.621956image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.567703image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.247898image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.967443image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.190810image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.123374image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.839085image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.609728image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.328620image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.005299image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.694390image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.641323image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.319833image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:34.031038image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.262232image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.195436image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.924508image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.684655image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.397596image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.069011image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.765016image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.707114image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.384438image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:34.096041image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:27.330996image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:28.264346image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.009535image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:29.755815image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:30.467396image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.136173image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:31.835419image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:32.775747image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-24T13:54:33.451482image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-04-24T13:54:36.229439image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
caratclaritycolorcutdepthpricetablexyz
carat1.000-0.346-0.2430.020-0.0030.9620.2050.9970.9960.994
clarity-0.3461.000-0.0420.042-0.071-0.180-0.147-0.343-0.338-0.348
color-0.243-0.0421.000-0.032-0.025-0.142-0.035-0.239-0.239-0.244
cut0.0200.042-0.0321.000-0.2880.0390.0730.0410.024-0.006
depth-0.003-0.071-0.025-0.2881.000-0.019-0.264-0.057-0.0590.072
price0.962-0.180-0.1420.039-0.0191.0000.1830.9630.9620.957
table0.205-0.147-0.0350.073-0.2640.1831.0000.2140.2060.170
x0.997-0.343-0.2390.041-0.0570.9630.2141.0000.9980.988
y0.996-0.338-0.2390.024-0.0590.9620.2060.9981.0000.987
z0.994-0.348-0.244-0.0060.0720.9570.1700.9880.9871.000